Overview of the INEX 2009 Ad Hoc Track

This paper gives an overview of the INEX 2009 Ad Hoc Track. The main goals of the Ad Hoc Track were three-fold. The first goal was to investigate the impact of the collection scale and markup, by using a new collection that is again based on a the Wikipedia but is over 4 times larger, with longer articles and additional semantic annotations. For this reason the Ad Hoc track tasks stayed unchanged, and the Thorough Task of INEX 2002–2006 returns. The second goal was to study the impact of more verbose queries on retrieval effectiveness, by using the available markup as structural constraints—now using both the Wikipedia’s layout-based markup, as well as the enriched semantic markup—and by the use of phrases. The third goal was to compare different result granularities by allowing systems to retrieve XML elements, ranges of XML elements, or arbitrary passages of text. This investigates the value of the internal document structure (as provided by the XML mark-up) for retrieving relevant information. The INEX 2009 Ad Hoc Track featured four tasks: For the Thorough Task a ranked-list of results (elements or passages) by estimated relevance was needed. For the Focused Task a ranked-list of non-overlapping results (elements or passages) was needed. For the Relevant in Context Task non-overlapping results (elements or passages) were returned grouped by the article from which they came. For the Best in Context Task a single starting point (element start tag or passage start) for each article was needed. We discuss the setup of the track, and the results for the four tasks.

Fast and effective focused retrieval

Building an efficient and an effective search engine is a very challenging task. In this paper, we present the efficiency and effectiveness of our search engine at the INEX 2009 Efficiency and Ad Hoc Tracks. We have developed a simple and effective pruning method for fast query evaluation, and used a two-step process for Ad Hoc retrieval. The overall results from both tracks show that our search engine performs very competitively in terms of both efficiency and effectiveness.